Data

GLO climate data stats summary

data.gov.au
Bioregional Assessment Program (Owned by)
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=http://data.gov.au/dataset/5a0a8f0f-fc83-4e5e-a07d-5c5ce1576e0a&rft.title=GLO climate data stats summary&rft.identifier=afed85e0-7819-493d-a847-ec00a318e657&rft.publisher=data.gov.au&rft.description=GLO climate data stats summary - Data File## **Abstract** \n\nThe dataset was derived by the Bioregional Assessment Programme from multiple source datasets. The source datasets are identified in the Lineage field in this metadata statement. The processes undertaken to produce this derived dataset are described in the History field in this metadata statement.\n\n\n\nVarious climate variables summary for all 15 subregions based on Bureau of Meteorology Australian Water Availability Project (BAWAP) climate grids. Including\n\n1. Time series mean annual BAWAP rainfall from 1900 - 2012.\n\n2. Long term average BAWAP rainfall and Penman Potentail Evapotranspiration (PET) from Jan 1981 - Dec 2012 for each month\n\n3. Values calculated over the years 1981 - 2012 (inclusive), for 17 time periods (i.e., annual, 4 seasons and 12 months) for the following 8 meteorological variables: (i) BAWAP_P (precipitation); (ii) Penman ETp; (iii) Tavg (average temperature); (iv) Tmax (maximum temperature); (v) Tmin (minimum temperature); (vi) VPD (Vapour Pressure Deficit); (vii) Rn (net radiation); and (viii) Wind speed. For each of the 17 time periods for each of the 8 meteorological variables have calculated the: (a) average; (b) maximum; (c) minimum; (d) average plus standard deviation (stddev); (e) average minus stddev; (f) stddev; and (g) trend.\n\n4. Correlation coefficients (-1 to 1) between rainfall and 4 remote rainfall drivers between 1957-2006 for the four seasons. The data and methodology are described in Risbey et al. (2009). \n\n\n\n\n\n\n\nAs described in the Risbey et al. (2009) paper, the rainfall was from 0.05 degree gridded data described in Jeffrey et al. (2001 - known as the SILO datasets); sea surface temperature was from the Hadley Centre Sea Ice and Sea Surface Temperature dataset (HadISST) on a 1 degree grid. BLK=Blocking; DMI=Dipole Mode Index; SAM=Southern Annular Mode; SOI=Southern Oscillation Index; DJF=December, January, February; MAM=March, April, May; JJA=June, July, August; SON=September, October, November. The analysis is a summary of Fig. 15 of Risbey et al. (2009).\n\n\n\nThere are 4 csv files here:\n\nBAWAP_P_annual_BA_SYB_GLO.csv\n\nDesc: Time series mean annual BAWAP rainfall from 1900 - 2012.\n\nSource data: annual BILO rainfall \n\n\n\nP_PET_monthly_BA_SYB_GLO.csv\n\nlong term average BAWAP rainfall and Penman PET from 198101 - 201212 for each month\n\n\n\nClimatology_Trend_BA_SYB_GLO.csv\n\nValues calculated over the years 1981 - 2012 (inclusive), for 17 time periods (i.e., annual, 4 seasons and 12 months) for the following 8 meteorological variables: (i) BAWAP_P; (ii) Penman ETp; (iii) Tavg; (iv) Tmax; (v) Tmin; (vi) VPD; (vii) Rn; and (viii) Wind speed. For each of the 17 time periods for each of the 8 meteorological variables have calculated the: (a) average; (b) maximum; (c) minimum; (d) average plus standard deviation (stddev); (e) average minus stddev; (f) stddev; and (g) trend\n\n\n\nRisbey_Remote_Rainfall_Drivers_Corr_Coeffs_BA_NSB_GLO.csv\n\nCorrelation coefficients (-1 to 1) between rainfall and 4 remote rainfall drivers between 1957-2006 for the four seasons. The data and methodology are described in Risbey et al. (2009). As described in the Risbey et al. (2009) paper, the rainfall was from 0.05 degree gridded data described in Jeffrey et al. (2001 - known as the SILO datasets); sea surface temperature was from the Hadley Centre Sea Ice and Sea Surface Temperature dataset (HadISST) on a 1 degree grid. BLK=Blocking; DMI=Dipole Mode Index; SAM=Southern Annular Mode; SOI=Southern Oscillation Index; DJF=December, January, February; MAM=March, April, May; JJA=June, July, August; SON=September, October, November. The analysis is a summary of Fig. 15 of Risbey et al. (2009).\n\n## **Dataset History** \n\nDataset was created from various BAWAP source data, including Monthly BAWAP rainfall, Tmax, Tmin, VPD, etc, and other source data including monthly Penman PET, Correlation coefficient data. Data were extracted from national datasets for the GLO subregion.\n\n\n\nBAWAP_P_annual_BA_SYB_GLO.csv\n\nDesc: Time series mean annual BAWAP rainfall from 1900 - 2012.\n\nSource data: annual BILO rainfall \n\n\n\nP_PET_monthly_BA_SYB_GLO.csv\n\nlong term average BAWAP rainfall and Penman PET from 198101 - 201212 for each month\n\n\n\nClimatology_Trend_BA_SYB_GLO.csv\n\nValues calculated over the years 1981 - 2012 (inclusive), for 17 time periods (i.e., annual, 4 seasons and 12 months) for the following 8 meteorological variables: (i) BAWAP_P; (ii) Penman ETp; (iii) Tavg; (iv) Tmax; (v) Tmin; (vi) VPD; (vii) Rn; and (viii) Wind speed. For each of the 17 time periods for each of the 8 meteorological variables have calculated the: (a) average; (b) maximum; (c) minimum; (d) average plus standard deviation (stddev); (e) average minus stddev; (f) stddev; and (g) trend\n\n\n\nRisbey_Remote_Rainfall_Drivers_Corr_Coeffs_BA_NSB_GLO.csv\n\nCorrelation coefficients (-1 to 1) between rainfall and 4 remote rainfall drivers between 1957-2006 for the four seasons. The data and methodology are described in Risbey et al. (2009). As described in the Risbey et al. (2009) paper, the rainfall was from 0.05 degree gridded data described in Jeffrey et al. (2001 - known as the SILO datasets); sea surface temperature was from the Hadley Centre Sea Ice and Sea Surface Temperature dataset (HadISST) on a 1 degree grid. BLK=Blocking; DMI=Dipole Mode Index; SAM=Southern Annular Mode; SOI=Southern Oscillation Index; DJF=December, January, February; MAM=March, April, May; JJA=June, July, August; SON=September, October, November. The analysis is a summary of Fig. 15 of Risbey et al. (2009).\n\n## **Dataset Citation** \n\nBioregional Assessment Programme (2014) GLO climate data stats summary. Bioregional Assessment Derived Dataset. Viewed 18 July 2018, http://data.bioregionalassessments.gov.au/dataset/afed85e0-7819-493d-a847-ec00a318e657.\n\n## **Dataset Ancestors** \n\n* **Derived From** [Natural Resource Management (NRM) Regions 2010](https://data.gov.au/data/dataset/1d54e38f-4051-4f0c-a350-c7dbd8eba65b)\n\n* **Derived From** [Bioregional Assessment areas v03](https://data.gov.au/data/dataset/96dbf469-5463-4f4d-8fad-4214c97e5aac)\n\n* **Derived From** [BILO Gridded Climate Data: Daily Climate Data for each year from 1900 to 2012](https://data.gov.au/data/dataset/7aaf0621-a0e5-4b01-9333-53ebcb1f1c14)\n\n* **Derived From** [Bioregional Assessment areas v01](https://data.gov.au/data/dataset/0fd0d820-30b3-451f-a126-a50040426999)\n\n* **Derived From** [Bioregional Assessment areas v02](https://data.gov.au/data/dataset/e414b1b3-c42e-42e9-9cc4-2093054aa35f)\n\n* **Derived From** [GEODATA TOPO 250K Series 3](https://data.gov.au/data/dataset/a0650f18-518a-4b99-a553-44f82f28bb5f)\n\n* **Derived From** [NSW Catchment Management Authority Boundaries 20130917](https://data.gov.au/data/dataset/0dc4272e-c081-4ed4-9645-aa336ffacd85)\n\n* **Derived From** [Geological Provinces - Full Extent](https://data.gov.au/data/dataset/0a064b3b-2a1e-4672-80d9-03333be67aad)\n\n* **Derived From** [GEODATA TOPO 250K Series 3, File Geodatabase format (.gdb)](https://data.gov.au/data/dataset/96ebf889-f726-4967-9964-714fb57d679b)\n\n&rft.creator=Bioregional Assessment Program&rft.date=2022&rft.coverage=POLYGON ((0 0, 0 0, 0 0, 0 0))&rft_rights=Creative Commons Attribution 4.0 International, http://creativecommons.org/licenses/by/4.0/, (c) Commonwealth of Australia (Bioregional Assessment Programme http://www.bioregionalassessments.gov.au), (c) Commonwealth of Australia (Geoscience Australia) 2014, (c) Office of Environment and Heritage NSW, (c) Commonwealth of Australia 2013, (c) Commonwealth of Australia (Bureau of Meteorology) 2014&rft_subject=Gloucester subregion&rft_subject=New South Wales&rft_subject=climatologyMeteorologyAtmosphere&rft.type=dataset&rft.language=English Access the data

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Creative Commons Attribution 4.0 International, Http://creativecommons.org/licenses/by/4.0/, (c) Commonwealth of Australia (bioregional Assessment Programme Http://www.bioregionalassessments.gov.au), (c) Commonwealth of Australia (geoscience Australia) 2014, (c) Office of Environment and Heritage Nsw, (c) Commonwealth of Australia 2013, (c) Commonwealth of Australia (bureau of Meteorology) 2014

Creative Commons Attribution 4.0 International, http://creativecommons.org/licenses/by/4.0/, (c) Commonwealth of Australia (Bioregional Assessment Programme http://www.bioregionalassessments.gov.au), (c) Commonwealth of Australia (Geoscience Australia) 2014, (c) Office of Environment and Heritage NSW, (c) Commonwealth of Australia 2013, (c) Commonwealth of Australia (Bureau of Meteorology) 2014

Brief description

## **Abstract** \n\nThe dataset was derived by the Bioregional Assessment Programme from multiple source datasets. The source datasets are identified in the Lineage field in this metadata statement. The processes undertaken to produce this derived dataset are described in the History field in this metadata statement.\n\n\n\nVarious climate variables summary for all 15 subregions based on Bureau of Meteorology Australian Water Availability Project (BAWAP) climate grids. Including\n\n1. Time series mean annual BAWAP rainfall from 1900 - 2012.\n\n2. Long term average BAWAP rainfall and Penman Potentail Evapotranspiration (PET) from Jan 1981 - Dec 2012 for each month\n\n3. Values calculated over the years 1981 - 2012 (inclusive), for 17 time periods (i.e., annual, 4 seasons and 12 months) for the following 8 meteorological variables: (i) BAWAP_P (precipitation); (ii) Penman ETp; (iii) Tavg (average temperature); (iv) Tmax (maximum temperature); (v) Tmin (minimum temperature); (vi) VPD (Vapour Pressure Deficit); (vii) Rn (net radiation); and (viii) Wind speed. For each of the 17 time periods for each of the 8 meteorological variables have calculated the: (a) average; (b) maximum; (c) minimum; (d) average plus standard deviation (stddev); (e) average minus stddev; (f) stddev; and (g) trend.\n\n4. Correlation coefficients (-1 to 1) between rainfall and 4 remote rainfall drivers between 1957-2006 for the four seasons. The data and methodology are described in Risbey et al. (2009). \n\n\n\n\n\n\n\nAs described in the Risbey et al. (2009) paper, the rainfall was from 0.05 degree gridded data described in Jeffrey et al. (2001 - known as the SILO datasets); sea surface temperature was from the Hadley Centre Sea Ice and Sea Surface Temperature dataset (HadISST) on a 1 degree grid. BLK=Blocking; DMI=Dipole Mode Index; SAM=Southern Annular Mode; SOI=Southern Oscillation Index; DJF=December, January, February; MAM=March, April, May; JJA=June, July, August; SON=September, October, November. The analysis is a summary of Fig. 15 of Risbey et al. (2009).\n\n\n\nThere are 4 csv files here:\n\nBAWAP_P_annual_BA_SYB_GLO.csv\n\nDesc: Time series mean annual BAWAP rainfall from 1900 - 2012.\n\nSource data: annual BILO rainfall \n\n\n\nP_PET_monthly_BA_SYB_GLO.csv\n\nlong term average BAWAP rainfall and Penman PET from 198101 - 201212 for each month\n\n\n\nClimatology_Trend_BA_SYB_GLO.csv\n\nValues calculated over the years 1981 - 2012 (inclusive), for 17 time periods (i.e., annual, 4 seasons and 12 months) for the following 8 meteorological variables: (i) BAWAP_P; (ii) Penman ETp; (iii) Tavg; (iv) Tmax; (v) Tmin; (vi) VPD; (vii) Rn; and (viii) Wind speed. For each of the 17 time periods for each of the 8 meteorological variables have calculated the: (a) average; (b) maximum; (c) minimum; (d) average plus standard deviation (stddev); (e) average minus stddev; (f) stddev; and (g) trend\n\n\n\nRisbey_Remote_Rainfall_Drivers_Corr_Coeffs_BA_NSB_GLO.csv\n\nCorrelation coefficients (-1 to 1) between rainfall and 4 remote rainfall drivers between 1957-2006 for the four seasons. The data and methodology are described in Risbey et al. (2009). As described in the Risbey et al. (2009) paper, the rainfall was from 0.05 degree gridded data described in Jeffrey et al. (2001 - known as the SILO datasets); sea surface temperature was from the Hadley Centre Sea Ice and Sea Surface Temperature dataset (HadISST) on a 1 degree grid. BLK=Blocking; DMI=Dipole Mode Index; SAM=Southern Annular Mode; SOI=Southern Oscillation Index; DJF=December, January, February; MAM=March, April, May; JJA=June, July, August; SON=September, October, November. The analysis is a summary of Fig. 15 of Risbey et al. (2009).\n\n## **Dataset History** \n\nDataset was created from various BAWAP source data, including Monthly BAWAP rainfall, Tmax, Tmin, VPD, etc, and other source data including monthly Penman PET, Correlation coefficient data. Data were extracted from national datasets for the GLO subregion.\n\n\n\nBAWAP_P_annual_BA_SYB_GLO.csv\n\nDesc: Time series mean annual BAWAP rainfall from 1900 - 2012.\n\nSource data: annual BILO rainfall \n\n\n\nP_PET_monthly_BA_SYB_GLO.csv\n\nlong term average BAWAP rainfall and Penman PET from 198101 - 201212 for each month\n\n\n\nClimatology_Trend_BA_SYB_GLO.csv\n\nValues calculated over the years 1981 - 2012 (inclusive), for 17 time periods (i.e., annual, 4 seasons and 12 months) for the following 8 meteorological variables: (i) BAWAP_P; (ii) Penman ETp; (iii) Tavg; (iv) Tmax; (v) Tmin; (vi) VPD; (vii) Rn; and (viii) Wind speed. For each of the 17 time periods for each of the 8 meteorological variables have calculated the: (a) average; (b) maximum; (c) minimum; (d) average plus standard deviation (stddev); (e) average minus stddev; (f) stddev; and (g) trend\n\n\n\nRisbey_Remote_Rainfall_Drivers_Corr_Coeffs_BA_NSB_GLO.csv\n\nCorrelation coefficients (-1 to 1) between rainfall and 4 remote rainfall drivers between 1957-2006 for the four seasons. The data and methodology are described in Risbey et al. (2009). As described in the Risbey et al. (2009) paper, the rainfall was from 0.05 degree gridded data described in Jeffrey et al. (2001 - known as the SILO datasets); sea surface temperature was from the Hadley Centre Sea Ice and Sea Surface Temperature dataset (HadISST) on a 1 degree grid. BLK=Blocking; DMI=Dipole Mode Index; SAM=Southern Annular Mode; SOI=Southern Oscillation Index; DJF=December, January, February; MAM=March, April, May; JJA=June, July, August; SON=September, October, November. The analysis is a summary of Fig. 15 of Risbey et al. (2009).\n\n## **Dataset Citation** \n\nBioregional Assessment Programme (2014) GLO climate data stats summary. Bioregional Assessment Derived Dataset. Viewed 18 July 2018, http://data.bioregionalassessments.gov.au/dataset/afed85e0-7819-493d-a847-ec00a318e657.\n\n## **Dataset Ancestors** \n\n* **Derived From** [Natural Resource Management (NRM) Regions 2010](https://data.gov.au/data/dataset/1d54e38f-4051-4f0c-a350-c7dbd8eba65b)\n\n* **Derived From** [Bioregional Assessment areas v03](https://data.gov.au/data/dataset/96dbf469-5463-4f4d-8fad-4214c97e5aac)\n\n* **Derived From** [BILO Gridded Climate Data: Daily Climate Data for each year from 1900 to 2012](https://data.gov.au/data/dataset/7aaf0621-a0e5-4b01-9333-53ebcb1f1c14)\n\n* **Derived From** [Bioregional Assessment areas v01](https://data.gov.au/data/dataset/0fd0d820-30b3-451f-a126-a50040426999)\n\n* **Derived From** [Bioregional Assessment areas v02](https://data.gov.au/data/dataset/e414b1b3-c42e-42e9-9cc4-2093054aa35f)\n\n* **Derived From** [GEODATA TOPO 250K Series 3](https://data.gov.au/data/dataset/a0650f18-518a-4b99-a553-44f82f28bb5f)\n\n* **Derived From** [NSW Catchment Management Authority Boundaries 20130917](https://data.gov.au/data/dataset/0dc4272e-c081-4ed4-9645-aa336ffacd85)\n\n* **Derived From** [Geological Provinces - Full Extent](https://data.gov.au/data/dataset/0a064b3b-2a1e-4672-80d9-03333be67aad)\n\n* **Derived From** [GEODATA TOPO 250K Series 3, File Geodatabase format (.gdb)](https://data.gov.au/data/dataset/96ebf889-f726-4967-9964-714fb57d679b)\n\n

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GLO climate data stats summary - Data File

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text: POLYGON ((0 0, 0 0, 0 0, 0 0))

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